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GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
16 years 25 days ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
16 years 25 days ago
A new evolutionary method for time series forecasting
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 25 days ago
An artificial immune network for multimodal function optimization on dynamic environments
Multimodal optimization algorithms inspired by the immune system are generally characterized by a dynamic control of the population size and by diversity maintenance along the sea...
Fabrício Olivetti de França, Fernand...
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
16 years 25 days ago
Takeover time curves in random and small-world structured populations
We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random ...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
16 years 25 days ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
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